Security Consultant - AI/ ML

Responsibilities:

• Conduct AI/ML security risk assessments across models, data pipelines, APIs, and deployment environments.
• Design and architect security controls for AI systems, including:
• Data privacy protections
• Model confidentiality and integrity measures
• Supply chain security for AI components
• Defenses against adversarial attacks and model poisoning
• Design and architect secure integrations of AI platforms like Open AI, CoPilot, Gemini, and Cloude into client environments 
• Develop and advise on AI governance frameworks covering security, ethics, privacy, and compliance.
• Provide recommendations for secure AI development lifecycle (Secure AILD) integration with MLOps and DevSecOps practices.
• Conduct threat modeling for AI-driven applications using frameworks such as MITRE ATLAS or OWASP AI Security guidelines.
• Assist in establishing monitoring and detection capabilities for AI-related threats.
• Ability to consult on how AI platforms like CoPilot, Claude and Gemini can be used to solve security problems in a client environment. 
• Guide organizations on regulatory compliance (e.g., GDPR, AI Act, NIST AI RMF, ISO/IEC 42001).
• Collaborate with data science, software engineering, IT security, and compliance teams to align security strategies.
• Deliver presentations, workshops, and executive briefings on AI security risks and mitigation strategies.
• Stay current on emerging threats, research, and best practices in AI/ML security.

Requirements:

• 2+ years of experience in AI/ML security, governance, or technical advisory.
• Strong understanding of:
• AI/ML fundamentals (models, data pipelines, inference)
• Cybersecurity controls and architecture (Zero Trust, cloud security, identity management)
• AI-specific threat vectors (data poisoning, model extraction, adversarial attacks)
• Familiarity with frameworks such as NIST AI RMF, MITRE ATLAS, OWASP Top 10 for LLMs/AI, or equivalent.
• Hands-on experience with cloud platforms (AWS, Azure, GCP) and securing cloud-based AI environments.
• Excellent verbal and written communication skills.
• Experience presenting complex topics to both technical and non-technical audiences.
• Preferred Qualifications:
• Certifications: CISSP, CCSP, GCPN, CCSK, or equivalent cybersecurity certifications.
• Certifications in AI or data science (e.g., TensorFlow, PyTorch, Microsoft AI certifications) a plus.
• Experience with large language models (LLMs), generative AI, or MLOps security.
• Familiarity with privacy-enhancing technologies (PETs) for AI (e.g., differential privacy, federated learning).